使用 R 聚合、排序和计算加权平均值

Question

我有两个数据框。一个是针对发票的详细信息 (df_inv)，另一个是针对发票的 collection 详细信息 (df_coll)。一张发票可能有多个 collections/vouchers。发票 table 大约有 30 列，目前我们只检查 3 列用于此计算（发票编号、预期金额、到期日）类似地 collections table 有多个变量，对于这种情况我们考虑 3 列（发票号、凭证日期、贷方金额） PS：一张 300 美元的发票可能会在 3 个不同的日期通过 3 张代金券（每张 100 美元）支付。贷记金额也可能小于或大于预期金额。根据发票table中的发票编号（唯一），我需要从collectiontable中找到其对应的凭证，根据凭证日期升序排列，找到付款延迟 (df_coll$VoucherDate - df_inv$DueDate)，然后计算每张发票的加权平均值。

x4 in df_inv，在 df_coll 中没有相应的条目。因此它将 return NA

加权平均计算（1 张发票和 2 张付款凭证）：

((1st pymt amt* 1st delay days)+ (2nd pymt amt* 2nd delay days))/((% of total credited amount)*(expected amount))

下面的示例数据，

发票Table(df_inv)

Invoice No  Expected Amount Due Date   
  x1    1400    02-01-2012
  x2    850     20-04-2012
  x3    1300    30-09-2012
  x4    1500    25-01-2013

Collections Table(df_coll)

Invoice No  Voucher Date    Credit Amount
      x1    26-11-2012  100
      x2    24-10-2012  200
      x1    11-05-2012  300
      x1    22-08-2013  100
      x2    12-07-2013  500
      x3    30-01-2014  600
      x2    24-06-2012  100
      x3    31-11-2012  700
      x1    29-02-2012  800

Answer 1

这是一个仅使用基础 R 的可能解决方案：

####################  Recreate your input data.frame's   ##################
df_inv <- 
data.frame(InvoiceNo=c("x1","x2","x3","x4"),
           Expected=c(1400,850,1300,1500),
           AmountDueDate=c("02-01-2012","20-04-2012","30-09-2012","25-01-2013"),
           stringsAsFactors=FALSE)
df_coll <- 
data.frame(InvoiceNo=c("x1","x2","x1","x1","x2","x3","x2","x3","x1"),
           VoucherDate=c("26-11-2012","24-10-2012","11-05-2012","22-08-2013",
                         "12-07-2013","30-01-2014","24-06-2012","30-11-2012","29-02-2012"),
           CreditAmount=c(100,200,300,100,500,600,100,700,800),
           stringsAsFactors=FALSE)
df_inv$AmountDueDate <- as.Date(df_inv$AmountDueDate,format='%d-%m-%Y')
df_coll$VoucherDate <- as.Date(df_coll$VoucherDate,format='%d-%m-%Y')
###########################################################################

m <- merge(df_inv,df_coll,by="InvoiceNo",all.x=TRUE,all.y=FALSE)
m$CrdAmntWeighted <- m$CreditAmount *  as.numeric(m$VoucherDate - m$AmountDueDate)
m$TotCredAmnt <- ave(m$CreditAmount,m$InvoiceNo,FUN=sum)
m$TotCrdAmntWeighted <- ave(m$CrdAmntWeighted,m$InvoiceNo,FUN=sum)
m$WeightedAvg <-  m$TotCrdAmntWeighted / ((m$TotCredAmnt / m$Expected) * m$Expected)

final <- m[!duplicated(m$InvoiceNo),c('InvoiceNo','Expected','TotCredAmnt','WeightedAvg')]

> final
   InvoiceNo Expected TotCredAmnt WeightedAvg
1         x1     1400        1300    137.0000
5         x2      850         800    334.8750
8         x3     1300        1300    257.6154
10        x4     1500          NA          NA

使用 R 聚合、排序和计算加权平均值

Aggregate, sort and calculate weighted average using R

sorting

aggregate

r

weighted-average